A random variable is one whose value is unknown or a function that assigns values to each of an experiment’s outcomes. A random variable can be discrete or continuous.

Probability density function is a statistical expression defining the likelihood of a series of outcomes for a continuous variable, such as a stock or ETF return.

Monte-Carlo-Simulations-on-an-Exponentially-Distributed-Random-Variable To use MATLAB and Monte Carlo simulations to demonstrate that the exponentially distributed random variable X with parameter ...

Definition and Marginal Distributions Discrete A discrete bivariate distribution represents the joint probability distribution of a pair of random variables. For discrete random variables with a ...

This paper is concerned with the determination of tight lower and upper bounds on the expectation of a convex function of a random variable. The classic bounds are those of Jensen and ...

Jensen gave a lower bound to Eρ (T), where ρ is a convex function of the random vector T. Madansky has obtained an upper bound via the theory of moment spaces of multivariate distributions. In ...